TLDR: Four Claude prompts built for the data complexity that makes Healthcare and MedTech selling harder than any other vertical — IDN and GPO structures with multiple buying entities, clinical versus administrative contacts that require completely different outreach, high contact turnover driven by health system consolidation, and accounts that go dark after a single personnel change. All four run on the Lusha connector for Claude.
Why data enrichment in Healthcare is a different problem
Selling into Healthcare and MedTech means navigating account structures that don’t exist anywhere else in B2B. An IDN like CommonSpirit or Ascension contains dozens of hospitals, each with its own administrative and clinical leadership. A GPO contract may route purchasing decisions through an entity that your CRM has never seen. The person who signs the contract isn’t always the person who evaluates it. The person who evaluates it isn’t always reachable.
Add high turnover — clinical staff rotate, health system mergers reshuffle org charts quarterly, and the administrator you met at a conference last year may have moved to a different system entirely — and you have a vertical where stale CRM data isn’t just an inconvenience, it’s a deal risk.
The four prompts in this article use Lusha’s verified contact data and firmographic layer to handle these challenges directly: verifying titles before outreach where clinical vs. administrative framing matters, mapping the full buying group across IDN and GPO structures, running territory data quality checks before each quarter, and scanning for health system accounts that have gone dark before they become churn. All four connect through the Lusha connector for Claude.
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Section 1: Getting the contact right before you reach out
Prompt 1: Verify a contact’s title before outreach
In Healthcare and MedTech, the difference between a clinical title and an administrative one isn’t cosmetic — it determines everything about how you frame the conversation. A Chief Medical Officer and a VP of Supply Chain at the same health system are both decision-makers, but reaching out to the CMO with a procurement message, or to the VP of Supply Chain with a clinical outcomes pitch, signals immediately that you don’t understand the account.
CRM titles in this vertical decay fast. Health system consolidations rename roles. Administrators move between IDN member hospitals. A contact entered as “Director of Value Analysis” twelve months ago may now be “AVP, Clinical Supply” — a different title, different scope, and different message required. This prompt checks Lusha’s current verified record against whatever is in the CRM before any outreach goes out, and flags exactly what changed and what it means for how you open the conversation.
<context>
I have a contact in my CRM and I'm not sure their title is current. I want to verify what Lusha has before I reach out — so I don't reference the wrong role or miss that they've been promoted.
My contact:
- Name: [NAME]
- Company: [COMPANY NAME OR DOMAIN]
- Title I have on file: [TITLE FROM CRM]
- Last updated in CRM: [DATE OR "UNKNOWN"]
</context>
<task>
1. Use Lusha to look up this contact:
- What is their current verified title?
- Are they still at the company?
- Has their title changed from what I have on file?
- How long have they been in the current role?
2. Classify the change (if any):
- SAME: title matches what I have on file
- PROMOTED: same company, higher seniority
- ROLE CHANGED: same company, different function or scope
- DEPARTED: no longer at the company — flag and find replacement if possible
- UNVERIFIED: Lusha can't confirm — needs manual check
3. If PROMOTED or ROLE CHANGED:
- Return the new title and note what changed
- Flag whether the change affects how I should open the conversation
4. Return the verification result with the current verified title, tenure, and one note on what (if anything) changes about the outreach.
</task>
<constraints>
- Only return what Lusha verifies.
- SAME is a useful output — it confirms the CRM is current.
- A promotion is not a reason to delay outreach — it's a reason to acknowledge it in the first line.
</constraints>Section 2: Mapping the full buying group across IDN and GPO structures
Healthcare and MedTech deals rarely close with a single contact. An IDN purchase typically involves a clinical champion (often a physician or CNO), an administrative approver (CFO or COO), a value analysis committee, and — for anything touching a GPO contract — a separate procurement pathway. Missing any one of these is a deal risk that compounds as the sales cycle progresses.
Prompt 2: Audit contact coverage gaps across named accounts
This prompt maps every required buying group role across your named accounts and returns a GREEN / AMBER / RED status per account — not based on how many contacts you have, but whether the right roles are covered. Three contacts at an IDN with no economic buyer is a CRITICAL GAP, not coverage. A STALE CONTACT — someone whose role has changed but who your CRM still shows as active — is flagged separately because it creates false confidence that’s harder to fix than a known gap.
In a Healthcare context, the buying group roles to specify might include: clinical champion (CMO, CNO, or senior physician), economic buyer (CFO or COO), value analysis lead, supply chain or procurement lead, and — for GPO-affiliated accounts — the GPO contract manager. Lusha returns a verified replacement contact for every gap found.
<context>
I manage a set of named accounts and I want to audit whether we have the right contacts mapped for each one — not just whether we have any contact, but whether we're covering the right roles in the buying group. Gaps in contact coverage mean gaps in deal control.
My named accounts:
- Account list: [PASTE COMPANY NAMES — one per line]
- What I sell: [PRODUCT / SOLUTION]
- Buying group roles I need covered: [e.g. Economic buyer / Technical evaluator / Champion / Procurement]
- Contacts I currently have: [PASTE NAME, TITLE, COMPANY — one per line]
</context>
<task>
1. For each account, use Lusha to map the current verified contacts in the relevant buying group roles:
- Who currently holds each role I need covered?
- Are my existing contacts still in the right roles?
- Are there roles I need covered but have no contact for?
2. For each account, return a coverage map:
- Role: COVERED (existing verified contact) / GAP (no contact for this role) / STALE (contact no longer in this role)
3. Prioritize the gaps:
- CRITICAL GAP: a must-have role with no verified contact — blocks deal progression
- IMPORTANT GAP: a should-have role missing — increases risk at current deal stage
- STALE CONTACT: someone I think I have but who's no longer in that role
4. For each GAP and STALE CONTACT: use Lusha to find the current verified contact for that role, with email and direct phone.
5. Return a contact coverage report:
- Per-account coverage map with GREEN / AMBER / RED status
- Critical gaps ranked by deal stage and ACV
- Replacement contacts found via Lusha for every gap
- Total accounts with at least one critical gap
</task>
<constraints>
- Coverage is role-specific, not headcount-specific. Having 3 contacts at an account but missing the economic buyer is a CRITICAL GAP.
- A STALE CONTACT is more dangerous than a GAP — it creates false confidence. Flag it prominently.
- If Lusha can't find a contact for a required role, flag it as a research task — don't leave it unmarked.
</constraints>Prompt 3: Get the full data quality report on a rep’s territory before the quarter starts
Health system territories are unusually volatile. A single IDN acquisition can reshuffle the org chart across multiple member hospitals simultaneously. A new VP of Supply Chain hired at the parent IDN may override purchasing decisions that were previously made at the facility level. Running a full territory data quality check before each quarter — not just checking whether contacts exist, but cross-referencing stale contacts against active deals and surfacing the ACV at risk — is the difference between a rep who knows their territory and one who finds out mid-cycle.
This prompt validates every contact in a rep’s territory via Lusha, flags DEPARTED and stale records, cross-references them against active deals to calculate the ACV at risk, and returns a clean-up priority list ranked by deal impact — plus a one-paragraph talking point the manager can use in the 1:1 before the quarter starts.
<context>
Before the quarter starts, I want a full data quality report on the contacts across a rep's territory — not just who's stale, but what the staleness is costing: which accounts are at risk, what the pipeline exposure is, and where to focus the clean-up effort first.
My territory:
- Rep name: [REP NAME]
- Contact list: [PASTE NAME, TITLE, COMPANY, LAST TOUCH DATE — one per line]
- Active deals in territory: [PASTE DEAL NAME, COMPANY, STAGE, ACV — one per line, OR "none"]
- Quarter starting: [Q1 / Q2 / Q3 / Q4 YEAR]
</context>
<task>
1. For each contact, use Lusha to check current status:
- Still at the company?
- Title current or changed?
- How long in the current role?
2. Categorize each contact:
- CURRENT: confirmed, verified — no action needed
- UPDATE NEEDED: still there, title changed — CRM update required
- DEPARTED: no longer at the company — find replacement if possible
- UNVERIFIED: Lusha can't confirm — flag for manual check
3. Cross-reference stale contacts against active deals:
- For any DEPARTED or UNVERIFIED contact tied to an active deal, flag as DEAL AT RISK
- Return the deal name, stage, ACV, and what specifically is stale
4. Return a territory data quality report:
- Overall data quality score: % of contacts CURRENT vs stale
- Contacts by category with counts
- DEAL AT RISK list: sorted by ACV descending
- Total ACV at risk from stale or unverified deal contacts
- Clean-up priority list: the 5 contacts to fix first, ranked by deal ACV impact
5. One-paragraph summary the manager can use in a 1:1 with the rep — what's the state of the territory data, what's at risk, and what needs to happen before Q[X] starts.
</task>
<constraints>
- Total ACV at risk is the number that matters most — lead with it.
- The 1:1 summary must be direct. Not "some contacts may need updating" but "3 of your active deals have stale or unverified contacts, totalling $X in ACV."
- If all contacts are CURRENT, say so — that's a good result worth noting.
</constraints>Section 3: Recovering accounts that have gone dark
Prompt 4: Find every account where the main contact has gone dark or left
In Healthcare and MedTech, accounts go dark for two distinct reasons that require completely different responses. The first is a contact departure — the administrator or clinical champion you were working with has moved to another health system, leaving the relationship with no anchor. The second is a gone-quiet account — the contact is still there, but engagement has dropped off for 45+ days, often because an internal priority shifted, a budget freeze hit, or someone new is now influencing the decision without your knowledge.
This prompt runs a monthly scan across your book, using Lusha to verify whether each primary contact is still at the account and Gmail to check when engagement last came in. Returns a DARK / COOLING / ACTIVE classification per account, surfaces replacement contacts for departed contacts via Lusha, and gives one specific re-engagement action per DARK account. The double-dark flag — contact gone and no engagement simultaneously — marks the highest-priority accounts to act on that week.
<context>
I want to find every account in my book where the primary contact relationship has gone dark — either the contact left, or engagement dropped off — before it turns into a churn risk or a dead deal I don't know about.
My book:
- Account list with primary contacts: [PASTE COMPANY, CONTACT NAME, TITLE — one per line]
- What counts as dark: [45+ DAYS NO REPLY / CONTACT DEPARTED / BOTH]
- Account type: [CUSTOMER / PROSPECT / BOTH]
</context>
<task>
1. For each account, check two things in parallel:
CONTACT STATUS (Lusha):
- Is the primary contact still at the company in the same role?
- If departed: find the most likely replacement via Lusha
ENGAGEMENT STATUS (Gmail):
- When was the last inbound email from this account?
- When was the last outbound email to this account?
- Is there an unanswered outbound email sitting unacknowledged?
2. Classify each account:
- DARK — CONTACT GONE: primary contact has left, no active thread
- DARK — GONE QUIET: contact still there but no inbound for 45+ days
- COOLING: last inbound was 21–44 days ago — not dark yet but trending that way
- ACTIVE: recent inbound, contact verified — no action needed
3. For DARK accounts:
- Return the specific reason (departed / gone quiet)
- Return replacement contact details if contact has departed (via Lusha)
- Suggest one specific re-engagement action
4. Return a dark accounts report:
- Summary: X DARK (contact gone), X DARK (gone quiet), X COOLING, X ACTIVE
- DARK accounts sorted by account value or deal stage
- For each DARK account: contact status, last touch date, replacement if found, recommended action
- Total ACV or ARR at risk from DARK accounts (if provided)
5. Flag any account that is DARK on both dimensions simultaneously — contact gone AND no engagement. These are the highest-priority accounts to act on this week.
</task>
<constraints>
- An account can be DARK for two different reasons — contact gone vs gone quiet. Both are risks but they require different responses.
- Don't surface COOLING accounts as urgent — they're a watch list, not an action list.
- The recommended action must be specific: not "reach out" but who to contact, how, and what angle.
</constraints>The pattern across all four prompts
Healthcare and MedTech data enrichment isn’t about cleaning a list once — it’s about maintaining an accurate picture of who’s at which entity, what role they hold, and whether the relationship is still active, across account structures that change constantly.
Every prompt in this article treats stale data as a revenue problem, not a hygiene problem. A wrong title before a clinical outreach isn’t just sloppy — it’s a signal that you don’t understand the account. A CRITICAL GAP in buying group coverage isn’t a CRM task — it’s a deal risk at the current stage. A double-dark account isn’t a follow-up item — it’s a churning relationship or dying deal that needs action this week, not next quarter.
The Lusha connector provides the verified contact and firmographic layer that makes all four prompts work — 300M+ verified contacts, compliant under GDPR, CCPA, SOC 2, ISO 27701, ISO 31700, and TRUSTe. No guessed fields, no format assumptions. If Lusha can’t verify it, the prompt flags it rather than inventing it.
Where these prompts live
All four prompts are in the data enrichment section of Lusha Plays.
